The impact of risk and protective factors on online teaching experience in high school Italian teachers during the COVID-19 pandemic

The lockdown due to COVID-19 in Italy resulted in the sudden closure of schools, with a shift from traditional teaching to the online one. Through an online questionnaire, this survey explores teachers' experience of online teaching, the level of risk factors (e.g., stress) and protective factors (e.g., locus of control) and their impact on satisfaction levels during the social distancing. One hundred seven high school teachers from Lombardy, an Italian region very affected by the COVID-19 outbreak, participated. Results show that depression and stress are the main predictors of satisfaction levels for online teaching. In addition, coping, locus of control and self-efficacy emerge as important protective factors. Finally, although there is great satisfaction with the online teaching experience, critical elements emerged. This study is relevant because it describes the critical elements of the online teaching experience, and identifies some protective factors and the main risk factors in teachers operating in an area strongly marked by social restrictions imposed by the pandemic. High school teachers emerge as a sub-group of the general population with specific psychological reactions. Considering the results, it is possible to suggest providing high-quality educational support and crisis-psychological oriented services to teachers, and help to maintain the psychological well-being.     

Stock Price Forecasting: An Echo State Network Approach

Forecasting stock prices using deep learning models suffers from problems such as low accuracy, slow convergence, and complex network structures. This study developed an echo state network (ESN) model to mitigate such problems. We compared our ESN with a long short-term memory (LSTM) network by forecasting the stock data of Kweichow Moutai, a leading enterprise in China’s liquor industry. By analyzing data for 120, 240, and 300 days, we generated forecast data for the next 40, 80, and 100 days, respectively, using both ESN and LSTM. In terms of accuracy, ESN had the unique advantage of capturing nonlinear data. Mean absolute error (MAE) was used to present the accuracy results. The MAEs of the data forecast by ESN were 0.024, 0.024, and 0.025, which were, respectively, 0.065, 0.007, and 0.009 less than those of LSTM. In terms of convergence, ESN has a reservoir state-space structure, which makes it perform faster than other models. Root-mean-square error (RMSE) was used to present the convergence time. In our experiment, the RMSEs of ESN were 0.22, 0.27, and 0.26, which were, respectively, 0.08, 0.01, and 0.12 less than those of LSTM. In terms of network structure, ESN consists only of input, reservoir, and output spaces, making it a much simpler model than the others. The proposed ESN was found to be an effective model that, compared to others, converges faster, forecasts more accurately, and builds time-series analyses more easily.     

人工神经网络技术在电工产品可靠性实验中的应用(理论部分)

本文简要介绍了人工神经网络，BP神经网络的结构、训练和学习规则以及人工神经网络非线性时间序列预测的应用概况。     

水下设备安装过程及其影响因素分析

为了提高水下设备安装精度与工作效率,基于海上工作经验及查阅国内外相关文献,对水下设备的安装过程进行了研究,其总体过程大致分为5个阶段,即装船固定、提升操作、穿越飞溅区、深水下放、落地坐放;分析了影响水下设备安装过程的主要因素,其中水深主要影响吊放系统和设备在水下的横向偏移;波浪载荷主要应用船舶的动态响应,在设备经历穿越飞溅区阶段时对设备及缆绳造成损伤的风险较大;水下设备自身参数主要影响安装方式和安装船舶的选用。     

西江流域压咸风险调度及其时空传递规律研究

枯水期珠江河口咸潮情势日益加重,径流不确定加剧了压咸风险,严重威胁沿线的供水安全。本文基于概率密度分布描述径流不确定性,构建了单源风险调度基本框架。以西江流域五座水库为研究对象,量化了预报误差与压咸风险的响应关系;揭示了压咸风险的时空传递规律;将压咸风险划分为3个等级;确定出各级风险越级传递的临界阈值。研究表明：随预报误差的增大,压咸风险提前且持续天数增加、风险率增大;压咸风险呈逐时段累积和从上游向下游、从支流向干流的时空传递规律;当预报误差超过±16%、±21%时,压咸风险从轻险越级至中险、中险越级至重险。研究成果对于西江流域压咸风险的调控和粤港澳大湾区的供水安全具有重要的应用价值。     

影响中小企业球铁质量稳定的因素

分析了影响中小企业球铁生产稳定性的关键因素,指出在一定的原材料条件下,目前中小型企业生产球铁存在的问题是温度偏低,孕育方法不当。     

类金刚石膜的制备及其影响因素

概述了近年来制类金刚石膜的新技术如双射频辉光放电（RF－RF）法，射频－直流辉光放电（RF－DC）法和微波－射频（MW－RF）法等，并且对影响类金刚石膜制备及性能的因素如基体材料，制备类金刚石膜时在膜中添加元素，类金刚石膜与基材之间的中间层等进行了较全面的分析。     

锡磷青铜合金水平连铸工艺参数的优化

铸造锡磷青铜合金组织中存在显微缩松、枝晶偏析和反偏析是冷加工报废的主要原因.通过连铸工艺参数的正交实验,建立了轧制成材率与主要工艺参数之间的神经网络描述,网络模型与遗传算法结合对工艺参数的组合进行了优化,改善了铸坯的组织,提高了轧制带材成材率.